1. Field of the Invention
The present invention relates generally to a content-providing method and system, and more particularly, to a content-providing method and system for effectively supplying a customized service by classifying data regarding usage behavior of users into representative content types, analyzing the representative types, and identifying time intervals in which the representative types consistently occur, without having to use user identification information.
2. Description of the Related Art
In conventional customized service systems, identification of a current user is assumed and the most appropriate service for the user is matched to the user based on a past use history of the user. However, when a customized content-providing service is provided via a system such as a Television (TV), which is a representative family device, it is difficult to provide an appropriate customized service due to the difficulty of individually identifying all users viewing content. When personalized recommendation is made based on viewing history of users, which is generally the case, data regarding a viewing history of several users with various tastes is mixed and stored in one device such as the TV, without classifying users according respective tastes. Therefore, such impersonalized recommendation may frequently lead to an inappropriate recommendation result.
Thus, there is a need for development of technology for storing and managing data, such as a user's viewing history, according to time intervals and a history of the user's behavior regarding an apparatus, and information searching technology and data-mining technology for extracting viewing patterns according to time intervals and analyzing a similarity between viewed content, based on the data.